Magnetic resonance technology for detecting groundwater is a new and developing geophysical detection technology, has attracted extensive attention and achieved rapid development due to its advantages of direct detection and quantitative assessment. So far, it has been gradually developed from the theoretical research to the development of a relatively mature detection instrument system, which has been utilized for field measurement in some areas and has successfully detected shallow groundwater resources. The detection is of great significance to improve the current status of water-shortage and predict geological disasters caused by groundwater. However, a relaxation of stimulated hydrogen proton in groundwater generates very small magnitude (nV-level 1 nV=10−9 V) of magnetic resonance signals is highly susceptible to interferences from various environmental noises. The random noise interference is difficult to remove because it has wide range of frequency band and is interlaced with the effective signal, and seriously affects the signal-to-noise ratio of the signal and results in large error of the post inversion interpretation. Consequently, effective eliminating of random noise and obtaining reliable magnetic resonance signals can improve the accuracy of the inversion interpretation results.
Chinese Patent CN104459809A discloses “a method of noise filtering from MRS oscillating signal based on independent component analysis”, which mainly focuses on the power frequency harmonic interference or some single frequency interference in MRS oscillating signal. Firstly, an MRS water detection apparatus is utilized for collecting an MRS signal; and the frequency of the power frequency harmonic interference or some single frequency interference contained in the collected signal is obtained by spectrum analysis, an underdetermined blind source separation issue is solved by constructing an input channel signal with a digital orthogonal method; then an independent component analysis is performed on the constructed input channel signal and the collected MRS signal together as input signals to obtain a separated MRS signal; finally a spectral correction method is utilized to solve the problem of the unsteady amplitude of the separated MRS signal, so as to extract a de-noised MRS signal. Chinese Patent CN104898172A discloses “a method of noise filtering from a MRS signal based on cross-correlation”. In the method, the characteristic of the non-correlation between noise and a sinusoidal signal of Larmor frequency and the correlation between an FID amplitude attenuation sinusoidal signal and the sinusoidal signal of Larmor frequency are utilized; the noise is filtered by the cross-correlation operation; then an envelope of the cross-correlation waveform is fitted, and the cross-correlation waveform having no noise is reconstructed; finally, a de-convolution algorithm is used for extracting FID signal from the MRS data. Chinese Patent CN104614778A discloses “a method of noise elimination from a MRS groundwater detecting signal based on ICA”. In the method, firstly, three sets of MRS response data are entered; Fourier Transform is performed on the three sets of data respectively, to determine the power frequency harmonics contained in the vicinity of the MRS center frequency in each set of data; then a sine function and a cosine function are constructed with the frequency which is the same as the power frequency harmonics and the length which is the same as the length of MRS corresponding data; an observed signal is composed of the functions and the MRS response data; an independent component analysis algorithm is utilized to separate each set of observed signals to obtain an unmixed signal; the data is reconstructed to eliminate the interference of the power frequency harmonics; then the three sets of MRS data with removed power frequency harmonics are processed as the observed signals using an ICA algorithm, to reduce the interference of the residual random noise. Jiang Chuandong's paper titled “Statistical stacking and adaptive notch filter to remove high-level electromagnetic noise from MRS measurements” was published in the Near Surface Geophysics [2011, 9(5), Pages 459-468]. Jiang uses a superposition method to suppress random noise, utilizes a magnetic resonance groundwater detecting system to collect signals multiple times (Ns times), and superposes all of individually collected signals; so that the signal-to-noise ratio can increase √{square root over (Ns)} times.
The method of noise filtering from a MRS signal based on independent component analysis as stated above can solve the underdetermined blind source issue and the amplitude uncertainties issue which are customary in the independent component analysis, and have the advantages of fast operation, high signal to-noise ratio, high practicability, etc., compared with conventional methods for de-noising MRS signals. However, the method can only implement filtering the inference of the power frequency and the inference of certain frequency, and cannot suppress the noise interference with a large frequency band distribution range, such as random noise. The method of noise filtering from a MRS oscillating signal based on cross-correlation as stated above can simultaneously suppress the power frequency and its harmonic noise, random noise and spike noise; however, the method mainly utilizes the characteristic of non-correlation between noise frequency and signal frequency, and cannot remove the overlap between the frequency component in the random noise and the signal frequency. The method of noise elimination from a MRS groundwater detecting signal based on ICA, as stated above, has no requirement of prior knowledge of the source signal and transmission channel, has no need of arranging a reference coil in the test process, and has the advantages of operation simple, convenient and high efficiency; however, the method requires at least three sets of data, complex calculation processes, a large amount of calculation; and it is difficult for those not skilled in the art to manipulate the method. The superposition method as stated above is the simplest and commonly-used method of random noise elimination from a magnetic resonance signal. In electromagnetic noise environment having the same intensity, the superposition method utilizes less superposition times to obtain the groundwater magnetic resonance signal with higher signal-to-noise ratio; but when the noise intensity is large, multiple superposing is needed and the measuring time is increased, resulting in lowering the working efficiency of the instrument and limited noise elimination effect.